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130626 ||| eng |
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|a 9783642240072
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| 100 |
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|a Lin, Dan
|e [editor]
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| 245 |
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|a Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R
|h Elektronische Ressource
|b Order-Restricted Analysis of Microarray Data
|c edited by Dan Lin, Ziv Shkedy, Daniel Yekutieli, Dhammika Amaratunga, Luc Bijnens
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| 250 |
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|a 1st ed. 2012
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| 260 |
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|a Berlin, Heidelberg
|b Springer Berlin Heidelberg
|c 2012, 2012
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| 300 |
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|a XV, 282 p. 96 illus., 4 illus. in color
|b online resource
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| 505 |
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|a Introduction -- Part I: Dose-response Modeling: An Introduction -- Estimation Under Order Restrictions -- The Likelihood Ratio Test -- Part II: Dose-response Microarray Experiments -- Functional Genomic Dose-response Experiments -- Adjustment for Multiplicity -- Test for Trend -- Order Restricted Bisclusters -- Classification of Trends in Dose-response Microarray Experiments Using Information Theory Selection Methods -- Multiple Contrast Test -- Confidence Intervals for the Selected Parameters -- Case Study Using GUI in R: Gene Expression Analysis After Acute Treatment With Antipsychotics
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| 653 |
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|a Pharmaceutical chemistry
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| 653 |
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|a Bioinformatics
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| 653 |
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|a Computational and Systems Biology
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| 653 |
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|a Statistics
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| 653 |
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|a Biostatistics
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| 653 |
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|a Pharmaceutics
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| 653 |
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|a Statistics
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| 653 |
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|a Mathematical statistics / Data processing
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| 653 |
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|a Statistics and Computing
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| 653 |
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|a Biometry
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| 700 |
1 |
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|a Shkedy, Ziv
|e [editor]
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| 700 |
1 |
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|a Yekutieli, Daniel
|e [editor]
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| 700 |
1 |
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|a Amaratunga, Dhammika
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Use R!
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| 028 |
5 |
0 |
|a 10.1007/978-3-642-24007-2
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-642-24007-2?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 519.5
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| 520 |
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|a This book focuses on the analysis of dose-response microarray data in pharmaceutical setting, the goal being to cover this important topic for early drug development and to provide user-friendly R packages that can be used to analyze dose-response microarray data. It is intended for biostatisticians and bioinformaticians in the pharmaceutical industry, biologists, and biostatistics/bioinformatics graduate students. Part I of the book is an introduction, in which we discuss the dose-response setting and the problem of estimating normal means under order restrictions. In particular, we discuss the pooled-adjacent-violator (PAV) algorithm and isotonic regression, as well as the likelihood ratio test and non-linear parametric models, which are used in the second part of the book. Part II is the core of the book. Methodological topics discussed include: · Multiplicity adjustment · Test statistics and testing procedures for the analysis of dose-response microarray data · Resampling-based inference and use of the SAM method at the presence of small-variance genes in the data · Identification and classification of dose-response curve shapes · Clustering of order restricted (but not necessarily monotone) dose-response profiles · Hierarchical Bayesian models and non-linear models for dose-response microarray data · Multiple contrast tests All methodological issues in the book are illustrated using four “real-world” examples of dose-response microarray datasets from early drug development experiments
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